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"intrinsically-aligned" artificial intelligence, where accuracy, fairness and explainability are all taken into account when selecting the "best" AI model. Requirements: The essential selection criteria include
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Computational background: engineering, physics, maths, or computer science. How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement explaining your motivation
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architected materials or metamaterials (MTM) that can undergo targeted non-linear response. You will develop a computational framework that can reveal novel Multiphysics (thermo-mechanical) MTM solutions
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of Warwick. This exciting project, co-supervised by Dr. Sagar Jilka and Dr. Vivek Furtado, focuses on developing a privacy-preserving Artificial Intelligence (AI) tool to predict the worsening of anxiety and
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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curriculum vitae (CV), transcripts and 300-word statement explaining your motivation for applying to this PhD Studentship to: Supervisor Review Form . Our supervisors will perform a comprehensive review to
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300-word statement explaining your motivation for applying to this PhD Studentship to: Supervisor Review Form . Our supervisors will perform a comprehensive review to long-list candidates. Deadline: 8
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combination of experimental work, rig development, and computational modelling, and will equip the student with a unique skill set highly relevant to both academic research and industrial careers such as
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). The Computer Science group is looking for students to work on one of the following projects Distributed Intelligence for Self-Organising Cloud–Edge Infrastructures Carbon-Conscious Resource Scheduling for AI Workloads
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, applied maths, or scientific computing as well as proficiency in Python/C++. Exposure to ML or automatic differentiation is a plus. You must be curious, collaborative, and motivated to turn methods